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4 biggest misconceptions about hiring data scientists

Sarah K. White | April 12, 2016
You probably think you know what you need out of a data scientist. However, if you believe in any of these common misconceptions, it might be time to reevaluate your business' expectations for current and future data scientists.

When you think of the perfect candidate for a data science role, a few preconceived notions come to mind. You want someone who is analytical, detail-oriented and intuitive -- all important qualities in a data scientist. But there is more to data science than being good with numbers -- the core of a data scientist's role involves influencing decision-makers within the business and guiding the future of the company.

While there are a lot logical traits that make a good data scientist, there are plenty of skills data scientists need that don't fall under the category of data. Ziad Nejmeldeen, senior vice president and chief scientist at the Infor Dynamic Science Labs, knows this better than anyone, having hired his own data scientists and helped guide the data strategies of numerous businesses at Infor. If you hold common misconceptions about data scientists, it might be time to reevaluate your strategy, according to Nejmeldeen.

It's just about collecting data

The ability to collect, organize and understand a wealth of data are crucial skills for any data scientist. However, data scientists also need the right skills to present that data in a useable format to others within the organization. In order to hire data scientists with strong presentation skills, Nejmeldeen began asking candidates to give a 30-minute presentation on something they are passionate about to test their presentation skills. Now he has a team of data scientists that have all the right skills to make the best use of data from start to finish.

Presentation skills are an oft-over looked quality in data scientist candidates, according to Nejmeldeen. "We live in a world where data is being collected by multiple sources in ever-increasing quantities; many associate the work of capturing and reporting on this data as data science -- I would not disagree with this notion, but I would say data science is much, much more."

Nejmeldeen says that if IT leaders ignore this data soft-skill, they do their business a disservice -- data won't get you anywhere if you can't convince the right people to embrace it. Your data scientists need to be confident in their data analysis and then be able to turn around and make it easy for executives, managers and anyone within the organization to actually utilize it. If your data scientists aren't going past just collecting and disseminating data, it might be time to adjust the job description.

Data scientists are developers

One of the biggest misconceptions about data scientists is that they're developers, according to Neimeldeen,. He says that if you expect a data scientist to not only collect data, understand it and then also design and develop solutions, your expectations might be a bit high. While there are certainly data scientists with a development background, you're going to want to leave that to the actual developers.

 

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